ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- All Subjects: Civil Engineering
Description
Ten regional climate models (RCMs) and atmosphere-ocean generalized model parings from the North America Regional Climate Change Assessment Program were used to estimate the shift of extreme precipitation due to climate change using present-day and future-day climate scenarios. RCMs emulate winter storms and one-day duration events at the sub-regional level. Annual maximum series were derived for each model pairing, each modeling period; and for annual and winter seasons. The reliability ensemble average (REA) method was used to qualify each RCM annual maximum series to reproduce historical records and approximate average predictions, because there are no future records. These series determined (a) shifts in extreme precipitation frequencies and magnitudes, and (b) shifts in parameters during modeling periods. The REA method demonstrated that the winter season had lower REA factors than the annual season. For the winter season the RCM pairing of the Hadley regional Model 3 and the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model had the lowest REA factors. However, in replicating present-day climate, the pairing of the Abdus Salam International Center for Theoretical Physics' Regional Climate Model Version 3 with the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model was superior. Shifts of extreme precipitation in the 24-hour event were measured using precipitation magnitude for each frequency in the annual maximum series, and the difference frequency curve in the generalized extreme-value-function parameters. The average trend of all RCM pairings implied no significant shift in the winter annual maximum series, however the REA-selected models showed an increase in annual-season precipitation extremes: 0.37 inches for the 100-year return period and for the winter season suggested approximately 0.57 inches for the same return period. Shifts of extreme precipitation were estimated using predictions 70 years into the future based on RCMs. Although these models do not provide climate information for the intervening 70 year period, the models provide an assertion on the behavior of future climate. The shift in extreme precipitation may be significant in the frequency distribution function, and will vary depending on each model-pairing condition. The proposed methodology addresses the many uncertainties associated with the current methodologies dealing with extreme precipitation.
ContributorsRiaño, Alejandro (Author) / Mays, Larry W. (Thesis advisor) / Vivoni, Enrique (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2013
Description
The Colorado River Basin (CRB) is the primary source of water in the
southwestern United States. A key step to reduce the uncertainty of future streamflow
projections in the CRB is to evaluate the performance of historical simulations of General
Circulation Models (GCMs). In this study, this challenge is addressed by evaluating the
ability of nineteen GCMs from the Coupled Model Intercomparison Project Phase Five
(CMIP5) and four nested Regional Climate Models (RCMs) in reproducing the statistical
properties of the hydrologic cycle and temperature in the CRB. To capture the transition
from snow-dominated to semiarid regions, analyses are conducted by spatially averaging
the climate variables in four nested sub-basins. Most models overestimate the mean
annual precipitation (P) and underestimate the mean annual temperature (T) at all
locations. While a group of models capture the mean annual runoff at all sub-basins with
different strengths of the hydrological cycle, another set of models overestimate the mean
annual runoff, due to a weak cycle in the evaporation channel. An abrupt increase in the
mean annual T in observed and most of the simulated time series (~0.8 °C) is detected at
all locations despite the lack of any statistically significant monotonic trends for both P
and T. While all models simulate the seasonality of T quite well, the phasing of the
seasonal cycle of P is fairly reproduced in just the upper, snow-dominated sub-basin.
Model performances degrade in the larger sub-basins that include semiarid areas, because
several GCMs are not able to capture the effect of the North American monsoon. Finally,
the relative performances of the climate models in reproducing the climatologies of P and
T are quantified to support future impact studies in the basin.
southwestern United States. A key step to reduce the uncertainty of future streamflow
projections in the CRB is to evaluate the performance of historical simulations of General
Circulation Models (GCMs). In this study, this challenge is addressed by evaluating the
ability of nineteen GCMs from the Coupled Model Intercomparison Project Phase Five
(CMIP5) and four nested Regional Climate Models (RCMs) in reproducing the statistical
properties of the hydrologic cycle and temperature in the CRB. To capture the transition
from snow-dominated to semiarid regions, analyses are conducted by spatially averaging
the climate variables in four nested sub-basins. Most models overestimate the mean
annual precipitation (P) and underestimate the mean annual temperature (T) at all
locations. While a group of models capture the mean annual runoff at all sub-basins with
different strengths of the hydrological cycle, another set of models overestimate the mean
annual runoff, due to a weak cycle in the evaporation channel. An abrupt increase in the
mean annual T in observed and most of the simulated time series (~0.8 °C) is detected at
all locations despite the lack of any statistically significant monotonic trends for both P
and T. While all models simulate the seasonality of T quite well, the phasing of the
seasonal cycle of P is fairly reproduced in just the upper, snow-dominated sub-basin.
Model performances degrade in the larger sub-basins that include semiarid areas, because
several GCMs are not able to capture the effect of the North American monsoon. Finally,
the relative performances of the climate models in reproducing the climatologies of P and
T are quantified to support future impact studies in the basin.
ContributorsGautam, Jenita (Author) / Mascaro, Giuseppe (Thesis advisor) / Vivoni, Enrique (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2018
Description
The fast pace of global urbanization makes cities the hotspots of population density and anthropogenic activities, leading to intensive emissions of heat and carbon dioxide (CO2), a primary greenhouse gas. Urban climate scientists have been actively seeking effective mitigation strategies over the past decades, aiming to improve the environmental quality for urban dwellers. Prior studies have identified the role of urban green spaces in the relief of urban heat stress. Yet little effort was devoted to quantify their contribution to local and regional CO2 budget. In fact, urban biogenic CO2 fluxes from photosynthesis and respiration are influenced by the microclimate in the built environment and are sensitive to anthropogenic disturbance. The high complexity of the urban ecosystem leads to an outstanding challenge for numerical urban models to disentangling and quantifying the interplay between heat and carbon dynamics.This dissertation aims to advance the simulation of thermal and carbon dynamics in urban land surface models, and to investigate the role of urban greening practices and urban system design in mitigating heat and CO2 emissions. The biogenic CO2 exchange in cities is parameterized by incorporating plant physiological functions into an advanced single-layer urban canopy model in the built environment. The simulation result replicates the microclimate and CO2 flux patterns measured from an eddy covariance system over a residential neighborhood in Phoenix, Arizona with satisfactory accuracy. Moreover, the model decomposes the total CO2 flux from observation and identifies the significant CO2 efflux from soil respiration. The model is then applied to quantify the impact of urban greening practices on heat and biogenic CO2 exchange over designed scenarios. The result shows the use of urban greenery is effective in mitigating both urban heat and carbon emissions, providing environmental co-benefit in cities. Furthermore, to seek the optimal urban system design in terms of thermal comfort and CO2 reduction, a multi-objective optimization algorithm is applied to the machine learning surrogates of the physical urban land surface model. There are manifest trade-offs among ameliorating diverse urban environmental indicators despite the co-benefit from urban greening. The findings of this dissertation, along with its implications on urban planning and landscaping management, would promote sustainable urban development strategies for achieving optimal environmental quality for policy makers, urban residents, and practitioners.
ContributorsLi, Peiyuan (Author) / Wang, Zhihua (Thesis advisor) / Vivoni, Enrique (Committee member) / Huang, Huei-Ping (Committee member) / Myint, Soe (Committee member) / Xu, Tianfang (Committee member) / Arizona State University (Publisher)
Created2021
Description
Quantifying the interactions among food, energy, and water (FEW) systems is crucial to support integrated policies for the nexus governance. Metropolitan areas are the main consumption and distribution centers of these three resources and, as urbanization continues, their role will become even more central. Despite this, the current understanding of FEW systems in metropolitan regions is limited. In this dissertation, the key factors leading to a more sustainable FEW system are identified in the metropolitan area of Phoenix, Arizona using the integrated WEAP-MABIA-LEAP platform. In this region, the FEW nexus is challenged by dramatic population growth, competition among increasing FEW demand, and limited water availability that could further decrease under climate change. First, it was shown that the WEAP platform allows the reliable simulations of water allocations from supply sources to demand sectors and that agriculture is a key stressor of the nexus, which will require additional groundwater (+83%) and energy (+15%) if cropland area is preserved over the next 50 years. Second, the climate change impacts on the food-water nexus were quantified by applying the WEAP-MABIA model with climate projections up to 2100 from 27 GCMs under different warming levels. It was found that the increases in temperature will lead to higher atmospheric evaporation demand that will, in turn, reduce crop production at a rate of -4.8% per decade. In the last part, the fully integrated WEAP-MABIA-LEAP platform was applied to investigate future scenarios of the FEW nexus in the metropolitan region. Several scenarios targeting each FEW sector were compared through sustainability indicators quantifying availability/consumption, reliability, and productivity of the three resources. Results showed that increasing renewable energy and changing cropping patterns will increase the FEW nexus sustainability compared to business-as-usual conditions. The findings of this dissertation, along with its analytical approach, support policy making towards integrated FEW governance and sustainable development.
ContributorsGuan, Xin (Author) / Mascaro, Giuseppe (Thesis advisor) / White, Dave (Committee member) / Vivoni, Enrique (Committee member) / Muenich, Rebecca (Committee member) / Arizona State University (Publisher)
Created2022